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      Wildfire smoke linked to vocal changes in wild Bornean orangutans

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          Summary

          Tropical peatlands are the sites of Earth’s largest fire events, with outsized contributions to greenhouse gases, toxic smoke, and haze rich with particulate matter. The human health risks from wildfire smoke are well known, but its effects on wildlife inhabiting these ecosystems are poorly understood. In 2015, peatland fires on Borneo created a thick haze of smoke that blanketed the region. We studied its effects on the long call vocalizations of four adult male Bornean orangutans ( Pongo pygmaeus wurmbii) in a peat swamp forest. During the period of heavy smoke, orangutans called less often and showed reduced vocal quality—lower pitch, increased harshness and perturbations, and more nonlinear phenomena—similar to changes in human smokers. Most of these changes persisted for two months after the smoke had cleared and likely signal changes in health. Our work contributes valuable information to support non-invasive acoustic monitoring of this Critically Endangered primate.

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          Highlights

          • Indonesia’s 2015 peatland fires caused the worst sustained air quality ever recorded

          • During and after the fires, orangutans called less and showed reduced vocal quality

          • Orangutans’ vocal changes likely signal illness or other shifts in their health

          Abstract

          Wildlife behavior; Biological sciences; Zoology

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          Most cited references67

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          Fitting Linear Mixed-Effects Models Using lme4

          Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
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            Fire in the Earth system.

            Fire is a worldwide phenomenon that appears in the geological record soon after the appearance of terrestrial plants. Fire influences global ecosystem patterns and processes, including vegetation distribution and structure, the carbon cycle, and climate. Although humans and fire have always coexisted, our capacity to manage fire remains imperfect and may become more difficult in the future as climate change alters fire regimes. This risk is difficult to assess, however, because fires are still poorly represented in global models. Here, we discuss some of the most important issues involved in developing a better understanding of the role of fire in the Earth system.
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              Observational Study of Behavior: Sampling Methods

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                Author and article information

                Contributors
                Journal
                iScience
                iScience
                iScience
                Elsevier
                2589-0042
                14 June 2023
                21 July 2023
                14 June 2023
                : 26
                : 7
                : 107088
                Affiliations
                [1 ]K. Lisa Yang Center for Conservation Bioacoustics, Cornell Lab of Ornithology, Cornell University, Ithaca, NY 14850, USA
                [2 ]Department of Anthropology, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA
                [3 ]Department of Social Sciences, Oxford Brookes University, Headington, Oxford OX3 0BP, UK
                [4 ]Gunung Palung Orangutan Conservation Program, West Kalimantan, Ketapang 78811, Indonesia
                [5 ]Department of Integrative Conservation, University of Georgia, Athens, GA 30602, USA
                [6 ]Department of Anthropology, University of Georgia, Athens, GA 30602, USA
                [7 ]Fakultas Biologi, Universitas Nasional, Jakarta 12520, Indonesia
                [8 ]Primate Research Center, Universitas Nasional, Jakarta 12520, Indonesia
                [9 ]Center for Human Evolutionary Studies, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA
                Author notes
                []Corresponding author erbivorous@ 123456gmail.com
                [10]

                Lead contact

                Article
                S2589-0042(23)01165-3 107088
                10.1016/j.isci.2023.107088
                10339020
                f6ed5eef-fd2b-4561-a690-f38baf58eb8a
                © 2023 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 7 December 2021
                : 23 June 2022
                : 7 June 2023
                Categories
                Article

                wildlife behavior,biological sciences,zoology
                wildlife behavior, biological sciences, zoology

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